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Software Engineer – Machine Learning (AI Training)

Offre en anglaisExpiré

Review and evaluate AI-generated machine learning code for correctness, efficiency, and scalability. Develop high-quality ML solutions and provide clear, developer-friendly explanations for model architecture and logic.

  • Télétravail
  • Toronto, Ontario, Canada
  • Publié 14 août 2026
  • Postuler avant le 13 sept. 2026
  • 1 poste

Ce poste est expiré

Ce poste chez Alignerr n’accepte plus de candidatures. L’offre originale reste disponible ci-dessous à titre de référence.

Expiré le 24 août 2026

Postes actuels chez Alignerr

Ces possibilités vérifiées acceptent toujours des candidatures.

Offre d’emploi originale

About The Role What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code? We're looking for experienced ML engineers in Toronto to evaluate AI-generated machine learning solutions — catching errors, improving quality, and helping frontier AI models get genuinely better at one of the hardest things they do. This is a fully remote, flexible contract role. Work asynchronously on your own schedule. No fixed hours, no meetings — just high-impact, expert work that matters. Organization: Alignerr Type: Hourly Contract Location: Remote (Canada-based) Commitment: Flexible, project-based What You'll Do Review and evaluate AI-generated machine learning code — including Python, TensorFlow, PyTorch, and scikit-learn — for correctness, efficiency, scalability, and clarity Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches Identify edge cases, ambiguities, and weaknesses in problem statements, datasets, or AI-generated responses Help set the quality bar for how AI understands and produces machine learning code Who You Are Deeply fluent in machine learning — you know your way around model development, data preprocessing, training pipelines, and deployment Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn Strong written communicator — able to explain complex ML concepts clearly and precisely Detail-oriented and rigorous — you catch what others miss and care about getting things right Self-motivated and comfortable working independently in an async environment Nice to Have 3–5+ years working on machine learning projects, pipelines, or MLOps Experience with model evaluation, cloud deployment, or production ML systems Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field Background in data labeling, RLHF, or other AI training workflows Prior experience with code review or technical writing Why Join Us Work on cutting-edge AI projects alongside leading research labs and top AI teams Fully remote and async — work when and where it suits you, with no minimum hour commitments beyond project needs Freelance autonomy with the structure of meaningful, task-based work Your contributions directly improve AI models used by top research labs and enterprise teams worldwide High-performing contributors take on expanded responsibilities and lead new programs Potential for ongoing work and contract extension as new projects launch

Ce que vous ferez

Review and evaluate AI-generated machine learning code for correctness, efficiency, and scalability. Develop high-quality ML solutions and provide clear, developer-friendly explanations for model architecture and logic.

Exigences

Requires deep fluency in machine learning frameworks like TensorFlow and PyTorch and strong written communication skills. A background in ML project pipelines or a degree in Computer Science or a related field is preferred.

Compétences indiquées

  • Apprentissage automatiqueSouhaitée
  • PythonSouhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

  • Machine Learning
  • Python
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Model Development
  • Data Preprocessing
  • Training Pipelines
  • MLOps
  • Technical Writing
  • Code Review
  • Model Evaluation
  • Cloud Deployment
  • RLHF
  • Data Labeling

Domaines d’emploi

  • Software
  • Technology
  • Engineering
  • Data & Analytics
  • Science & Research

Renseignements supplémentaires

Formation minimale
Baccalauréat
Expérience minimale
2+ ans
Postuler avant le
13 sept. 2026
Langue de l’offre
anglais
Heures de travail
40 heures par semaine
Exigences de lieu
Country, Toronto, Ontario, Canada
Niveau d’expérience
Mid-Senior level